Edoxaban dosing patterns in real life practice – Results from the DRESDEN NOAC REGISTRY
Bibliographic record
Abstract
Edoxaban is a non-vitamin K dependent oral anticoagulant (NOAC) licensed for venous thromboembolism treatment or stroke prevention in atrial fibrillation. Effectiveness and safety of edoxaban depends on adequate dosing, for which renal function, body weight and drug-drug interactions are important. Edoxaban dosing pattern data outside of clinical trials are scarce. Using data from the prospective DRESDEN NOAC REGISTRY we analysed dosing of 1635 edoxaban patients. Between January 2016 and May 2021, 1652 edoxaban treated patients were enrolled and 1635 patients included in the dosing analysis. At baseline, 1257 patients (76.9%) received edoxaban 60 mg daily, 378 patients (23.1%) 30 mg daily. Patients receiving edoxaban 60 mg were more often male, younger and less often had concomitant diseases such as cancer, renal impairment or organ transplantation. Edoxaban dosing was according to label in 1432 (87.6%) and not according to label in 203 patients (6.5% non-recommended 60 mg and 5.9% non-recommended 30 mg). Renal impairment was the dominating reason for dose adjustment, followed by body weight ≤60 kg. Edoxaban dosing was more often adequate in patients younger than 75 years and in male patients compared to older or female patients. Taken together, edoxaban dosing was adequate in up to 90% of patients, with renal impairment being the most important factor for dose reduction. Use of strong P-gp inhibitors was a rare finding and dose reduction was appropriately performed in the majority of these patients. Inadequate dosing seems more frequent in female or older patients and in transplant recipients, indicating areas for further research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".